Skip to main content

Toolbox Python per l'analisi dei dati di laboratorio

Project description

mespy

Documentation: giancarmine-sparso.github.io/mespy

Small Python toolbox for mechanics laboratory data analysis.

mespy started as a set of helper functions that kept reappearing across mechanics lab notebooks and classroom scripts: loading CSV measurements, computing descriptive and weighted statistics, plotting histograms, and running linear fits with uncertainties. The library brings those recurring tasks together into a single typed package with a small public API that is easy to use in notebooks, scripts, and teaching material.

What It Provides

  • CSV loading with explicit missing-data policies
  • Descriptive and weighted statistics for one-dimensional data
  • Histogram plotting for quick exploratory analysis
  • Weighted linear fitting with a typed result object
  • Clear validation errors instead of silent nan propagation

Public API

The root package exports:

  • load_csv
  • median
  • weighted_mean
  • variance
  • covariance
  • standard_deviation
  • histogram
  • lin_fit

The root namespace stays intentionally small. Additional public types, such as mespy.fit_utils.LinearFitResult, live in submodules.

Installation

mespy requires Python >= 3.12.

pip install git+https://github.com/giancarmine-sparso/mespy.git

Development Setup

To set up a local development environment:

Unix / macOS

git clone https://github.com/giancarmine-sparso/mespy
cd mespy
make setup

To activate the virtual environment manually:

source .venv/bin/activate

Windows

git clone https://github.com/giancarmine-sparso/mespy
cd mespy
python -m venv .venv
.venv\Scripts\activate
pip install -e ".[dev]"

Documentation

The Sphinx source lives in docs/source, and the generated site is written to docs/build/html.

Build the documentation with:

make docs

The generated site includes both English and Italian outputs, with English as the default landing page. The documentation also includes usage examples for the available functions. Complete usage workflows and notebooks are available in docs/source/examples.

Project Structure

mespy/
├── .github/
│   └── workflows/          # automation for documentation publishing
├── data/
│   └── reference/          # reference datasets used by tests and examples
├── docs/
│   ├── source/             # Sphinx source, examples, and translations
│   ├── Makefile
│   └── make.bat
├── figures/                # exported example figures
├── src/
│   └── mespy/              # library package
├── tests/                  # pytest suite
├── tools/                  # release and smoke-test helpers
├── LICENSE
├── Makefile                # local setup, testing, release, and docs tasks
├── pyproject.toml          # package metadata and dependencies
├── README.md
└── uv.lock

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

mespy-1.1.5.tar.gz (24.0 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

mespy-1.1.5-py3-none-any.whl (20.6 kB view details)

Uploaded Python 3

File details

Details for the file mespy-1.1.5.tar.gz.

File metadata

  • Download URL: mespy-1.1.5.tar.gz
  • Upload date:
  • Size: 24.0 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.12.3

File hashes

Hashes for mespy-1.1.5.tar.gz
Algorithm Hash digest
SHA256 f95d76e2b54a4842d6d53ca013c8f7bd25761ba7118866e1e83c1647d3db1250
MD5 699b1529e372977d626cdb0550302b49
BLAKE2b-256 e01f1ea8e936cfebcff8fe634dcd55bc6b11454a6b846d09c08b61b8fc9feb52

See more details on using hashes here.

File details

Details for the file mespy-1.1.5-py3-none-any.whl.

File metadata

  • Download URL: mespy-1.1.5-py3-none-any.whl
  • Upload date:
  • Size: 20.6 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.12.3

File hashes

Hashes for mespy-1.1.5-py3-none-any.whl
Algorithm Hash digest
SHA256 7b25db86f5f8015610915d8feaf55e0c1bb11f811cfa9869a771eb2b775b622b
MD5 d88114b363e75a09999a200089819df5
BLAKE2b-256 dd2b32107648a126c1f932fc18c8f20cdb07b1a0555944abd27049c8e789add2

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page